kioku-rl 0.1.0

Cognitive science-inspired reinforcement learning research library

Kioku

DQN

Using:

• DQN
• Double q networks
• Epsilon decay

Masters cartpole after only 92 episodes?

A2C

Using:

• A2C
• GAE
• N-Step Returns (with GAE)

Note that A2C is much less sample efficient than DQN and the SOTA (PPO, TD3, SAC).

Lunar Lander:

PPO

...did I just successfully implement PPO?

Using:

• PPO (basically A2C with a few extra steps)
• GAE
• N-Step Returns (with GAE)
• Mini-batch learning
• Multiple learning iterations per batch

As sample efficient as DQN? (minus the memory)

Lunar Lander: